This reporsitory includes three files: one jupyter notebook(disposition-effect.ipynb), two datasets(sample1.Rdata and sample2.Rdata) and one readme.txt file.

The comments for variables in two Rdata files is below:
- cube.symbol: id of traders in Xueqiu
- date: the calender date.
- trd.num: trading number a trader have executed.
- mmt: momentum of market monthly, which is UMD factor made by Carhart(1997).
- active.day: the days number a portfolio have existed.
- hold.period: a stock's holding period that a trader have bought, which calculating daily.
- pre.period: the period from date first trading to date first following someone.
- stkcd: Chinese A-share stock id.
- sale: a trader's stock at that date is sold(value is 1) or not(value is 0).
- gain: a trader's stock at that date is benifit(value is 1) or not(value is 0).
- follow.date: the date a trader first follow someone.
- post.follow: the date is after(value is 1) the first following date of a trader or not(value is 0).
- pre.follow: the date is before(value is 1) the first following date of a trader or not(value is 0).
- cntra: whoms' average centrality a trader follows to
- followings: the number of a trader's following, which calculating daily.
- followers: the number a trader's fans, which calculating daily. 
- ret: the daily return per portfolio.

You can use R to read the two datasets, and then run the jupyter notebook to replicate graphs and tables.